New benchmark ranks search APIs for AI agents on quality, cost, and speed

Artificial Analysis has launched a new evaluation framework titled the "Search Index." This benchmark assesses search API providers based on their suitability for AI agent workflows, specifically measuring performance across quality, cost efficiency, and response speed.

The evaluation involved testing seven different providers using the GPT-5.6 Luna model. According to the report, Parallel, Exa, and Firecrawl emerged as the top performers among the tested services, distinguishing themselves in the specific metrics outlined by the benchmark.

As AI agents increasingly rely on real-time information retrieval to function effectively, the underlying search infrastructure becomes a critical component. Standardizing how these APIs are measured helps developers and enterprises make informed decisions when building agentic applications.

This release highlights the growing specialization within the AI tooling ecosystem. Beyond general language models, the focus is shifting toward the supporting services that enable agents to access and process external data reliably.

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